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eNauka >  Results >  The model for grain wheat yield prediction at high spatial resolution based on physical-geographical properties and satellite vegetation indices
Title: The model for grain wheat yield prediction at high spatial resolution based on physical-geographical properties and satellite vegetation indices
Authors: Blagojević, Dragana  ; Pajević, Nina  ; Mimić, Gordan  ; Ćuković, Stefanija  ; Marković, Slobodan  ; Maestrini, Bernardo; Brdar, Sanja  
Issue Date: 2025
Publication: Geocarto International
ISSN: 1010-6049 Geocarto International Search Idenfier
Publisher: Taylor and Francis Ltd.
Type: Article
Collation: vol. 40 br. 1 str. 1-21
DOI: 10.1080/10106049.2025.2493741
WoS-ID: 001478006300001
Scopus-ID: 2-s2.0-105003777540
URI: https://grafar.grf.bg.ac.rs/handle/123456789/3722
https://enauka.gov.rs/handle/123456789/979149
Project: This work was supported by the Ministry of Education, Science and Technological Development of theRepublic of Serbia (Grant No. 451-03-136/2025-03/ 200358), Provincial Secretariat for Higher Educationand Scientific Research of the Autonomous Province of Vojvodina through the project ’Development of adecision support system for agricultural production using data fusion and artificial intelligence’ (GrantNo. 003074633 2024 09418 003 000 000 001 04 002) and European Union’s Horizon 2020 research andinnovation programmes ANTARES project (SGA-CSA. No. 739570 under FPA No. 664387, https://doi.org/10.3030/739570) through ANTARES Joint Strategic Research Agenda between BioSense Instituteand Wageningen University & Research.
Ministarstvo nauke, tehnološkog razvoja i inovacija Republike Srbije, institucionalno finansiranje - 200358 (BioSense institut)
ANTARES - Centre of Excellence for Advanced Technologies in Sustainable Agriculture and Food Security
ANTARES - Centre of Excellence for Advanced Technologies in Sustainable Agriculture and Food Security
Metadata source: (Preuzeto iz CrossRef-a) Ćuković, Stefanija
M-category: 
21M21

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